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Description
UST IQ for AMI Analytics streamlines the entire data engineering process, managing everything from the ingestion of large-scale, high-frequency metering data to delivering comprehensive insights, allowing AMI business operations to prioritize essential decision-making over IT infrastructure concerns. It efficiently collects both real-time and historical data, including meter readings, events, alarms, GIS information, and external data sources, and transforms this information into query-ready formats using a cloud-native, microservices architecture. This setup supports self-service querying, location-aware and role-specific analytics, and proactive exception management, providing operations teams with crucial insights regarding network anomalies, meter performance, outages, and environmental data such as seismic activity or weather patterns. By doing so, it enhances the ability to optimize field crew deployment, avert expensive failures, and improve restoration efforts. The system processes vast quantities of data, handling hundreds of millions of records each day through low-latency micro-batching, typically in 5-minute intervals, while also offering features like 30-day rolling averages and alert-triggered notifications to further support operational efficiency. This comprehensive approach not only accelerates data processing but also ensures that actionable insights are readily available when needed, ultimately leading to improved operational effectiveness.
Description
VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data.
It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries.
VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data.
The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources.
Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.
API Access
Has API
API Access
Has API
Integrations
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
MySQL
dbt
Integrations
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
MySQL
dbt
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
UST
Country
United States
Website
www.ust.com/en/what-we-do/digital-transformation/data-analytics/ust-iq/ami
Vendor Details
Company Name
VeloDB
Founded
2023
Country
Singapore
Website
www.velodb.io
Product Features
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge